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Absorptive Capacity and the Growth and Investment Effects of Regional Transfers: A Regression Discontinuity Design with Heterogeneous Treatment Effects
Author(s) -
Sascha O. Becker,
Peter Egger,
Maximilian von Ehrlich
Publication year - 2013
Publication title -
american economic journal economic policy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 7.868
H-Index - 62
eISSN - 1945-7731
pISSN - 1945-774X
DOI - 10.1257/pol.5.4.29
Subject(s) - regression discontinuity design , economics , per capita , variance (accounting) , human capital , per capita income , investment (military) , econometrics , demographic economics , regression , absorptive capacity , discontinuity (linguistics) , monetary economics , statistics , mathematics , economic growth , population , demography , mathematical analysis , industrial organization , politics , political science , law , accounting , sociology
Transfers to individuals, firms, and regions are often regulated by threshold rules, giving rise to a regression discontinuity design. An example are transfers provided by the European Commission to regions of EU member states below a certain income level. Researchers have focused on estimation of the average treatment effect of this program, assuming that it does not vary in a systematic way across units. We suggest a regression discontinuity design which allows for parametric or nonparametric identification of heterogeneous average treatment effects that systematically vary with observable characteristics in order to shed light on the role of absorptive capacity in determining the impact of regional transfers on economic growth across regions in the European Union. The results suggest that only about 47% of the regions, namely those with a sufficiently high endowment with human capital and a high quality of government, are able to turn transfers under the Union's Objective 1 Structural Funds programme into faster growth. Those regions are the ones which are responsible for a positive average effect of the programme.

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